Robust predictive controller based on an uncertain neural networks model

This paper deals with the robust predictive control of nonlinear systems. The behavior of the nonlinear system is described by an uncertainty Feedforward neural networks model, i.e. each output layer's parameter is uncertain. The control problem is formulated as a minimax optimization one which...

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Bibliographic Details
Published inThe 2010 International Joint Conference on Neural Networks (IJCNN) pp. 1 - 6
Main Authors Mnasser, A, Bouani, F, Ksouri, M
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2010
Subjects
Artificial neural networks
Computational modeling
Cost function
Mathematical model
Predictive models
Uncertainty
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Summary:This paper deals with the robust predictive control of nonlinear systems. The behavior of the nonlinear system is described by an uncertainty Feedforward neural networks model, i.e. each output layer's parameter is uncertain. The control problem is formulated as a minimax optimization one which is a non convex problem. The performances of the proposed controller are illustrated and compared to a classical PI controller by a simulation example.
ISBN:9781424469161
1424469163
ISSN:2161-4393
2161-4407
DOI:10.1109/IJCNN.2010.5596370